DeXe Protocol engagement report

Best tweets

• Jul 6, 202639x their median

  BonkDAO was the target of a malicious governance proposal resulting in an estimated $20M worth of BONK tokens being drained from the BonkDAO treasury. During the investigation, BonkDAO identified the exchange wallets used to purchase BONK ahead of the proposal. BonkDAO is currently actively working with exchanges, bridges and Solana Foundation to best manage the situation. Law enforcement has been notified. BonkDAO continues to work with relevant parties to recover funds and identify those responsible.

  1.9K2409675462.7M viewsView on X
• Feb 21, 202630x their median

  "AI becomes the government" is dystopian: it leads to slop when AI is weak, and is doom-maximizing once AI becomes strong. But AI used well can be empowering, and push the frontier of democratic / decentralized modes of governance. The core problem with democratic / decentralized modes of governance (including DAOs on ethereum) is limits to human attention: there are many thousands of decisions to make, involving many domains of expertise, and most people don't have the time or skill to be experts in even one, let alone all of them. The usual solution, delegation, is disempowering: it leads to a small group of delegates controlling decision-making while their supporters, after they hit the "delegate" button, have no influence at all. So what can we do? We use personal LLMs to solve the attention problem! Here are a few ideas: ## Personal governance agents If a governance mechanism depends on you to make a large number of decisions, a personal agent can perform all the necessary votes for you, based on preferences that it infers from your personal writing, conversation history, direct statements, etc. If the agent is (i) unsure how you would vote on an issue, and (ii) convinced the issue is important, then it should ask you directly, and give you all relevant context. ## Public conversation agents Making good decisions often cannot come from a linear process of taking people's views that are based only on their own information, and averaging them (even quadratically). There is a need for processes that aggregate many people's information, and then give each person (or their LLM) a chance to respond *based on that*. This includes: * Inferring and summarizing your own views and converting them into a format that can be shared publicly (and does not expose your private info) * Summarizing commonalities between people's inputs (expressed as words), similar to the various LLM+https://t.co/Nzord33s0z ideas ## Suggestion markets If a governance mechanism values "high-quality inputs" of any type (this could be proposals, or it could even be arguments), then you can have a prediction market, where anyone can submit an input, AIs can bet on a token representing that input, and if the mechanism "accepts" the input (either accepting the proposal, or accepting it as a "unit" of conversation that it then passes along to its participant), it pays out $X to the holders of the token. Note that this is basically the same as https://t.co/nUL0HyTyK2 ## Decentralized governance with private information One of the biggest weaknesses of highly decentralized / democratic governance is that it does not work well when important decisions need to be made with secret information. Common situations: (i) the org engaging in adversarial conflicts or negotiations (ii) internal dispute resolution (iii) compensation / funding decisions. Typically, orgs solve this by appointing individuals who have great power to take on those tasks. But with multi-party computation (currently I've seen this done with TEEs; I would love to see at least the two-party case solved with garbled circuits https://t.co/PIY2LZtbeK so we can get pure-cryptographic security guarantees for it), we could actually take many people's inputs into account to deal with these situations, without compromising privacy. Basically: you submit your personal LLM into a black box, the LLM sees private info, it makes a judgement based on that, and it outputs only that judgement. You don't see the private info, and no one else sees the contents of your personal LLM. ## The importance of privacy All of these approaches involve each participant making use of much more information about themselves, and potentially submitting much larger-sized inputs. Hence, it becomes all the more important to protect privacy. There are two kinds of privacy that matter: * Anonymity of the participant: this can be accomplished with ZK. In general, I think all governance tools should come with ZK built in * Privacy of the contents: this has two parts. First, the personal LLM should do what it can to avoid divulging private info about you that it does not need to divulge. Second, when you have computation that combines multiple LLMs or multiple people's info, you need multi-party techniques to compute it privately. Both are important.

  1.9K272554129308K viewsView on X
• Jun 16, 20264.7x their median

  DAOs were a failure in the last era of crypto. But it may have just been the wrong time for them. Two big things are different now: (1) regulatory clarity and (2) AI agents. We spent the last 10 years rediscovering the hard way that direct democracy is a bad idea. Turns out, nobody wakes up in the morning eager to adjudicate risk parameters or protocol updates. It didn't help that it was illegal to experiment with different DAO structures. The vicious hostility of Biden and Gensler toward the space killed all innovation. But it's a new day. It is once again legal to experiment. You could choose to play with forms of representative democracy, or multi-cameral systems, or hybrids of permissioned and permissionless participation. Not to mention, AI agents can now step into many kinds of roles that humans will never want to perform. They may help DAOs live up to their name by making them truly Autonomous. The design space for new DAOs is infinite, for they are just software. What new experiments are people running?

  288341002373K viewsView on X
• Jul 28, 20264.4x their median

  Dear community, We are aware of questions around the recent DEXE volatility. The DeXe protocol operated normally throughout, with no exploit or security breach. Neither the DeXe Foundation nor the DAO treasury sold DEXE into the move, and the treasury received no proceeds from it. We do not have a verified explanation for why the price rose and fell, and we will not speculate about the cause. Our focus remains on shipping. Any verified updates will be shared through official DeXe channels.

  18129196549K viewsView on X
• May 29, 20263.3x their median

  Weekly Top Gainers 1️⃣ Stellar (@StellarOrg): +42.28% 2️⃣ DeXe (@DexeNetwork): +32.97% 3️⃣ Audiera (@Audiera_web3): +25.12% 4️⃣ Humanity (@Humanityprot): +22.99% 5️⃣ Injective (@Injective_): +21.81% 6️⃣ Defi App (@defiapp): +21.76% 7️⃣ Stable (@stable): +19.20% 8️⃣ Falcon Finance (@falconfinance): +18.64% 9️⃣ Midnight (@MidnightNtwrk): +14.81% 🔟 dYdX (@dYdX): +13.40%

  1747359735K viewsView on X
• Mar 20, 20262.5x their median

  1️⃣ DeXe (@DexeNetwork): +47.33% 2️⃣ Audiera (@Audiera_web3): +45.38% 3️⃣ BUILDon (@BUILDonBsc_AI): +38.49% 4️⃣ River (@RiverdotInc): +32.73% 5️⃣ MemeCore (@MemeCore_M): +24.87% 6️⃣ Fartcoin (@FartCoinOfSOL): +24.25% 7️⃣ Kaspa (@kaspaunchained): +23.33% 8️⃣ Bittensor (@opentensor): +20.81% 9️⃣ Zebec Network (@Zebec_HQ): +19.62% 🔟 Quant (@quant_network): +18.70%

  1523642325K viewsView on X
• Aug 25, 20261.8x their median

  Use case #1: from zero to a live DAO on mainnet. This is what DeXe was built for. #DeXe #DAO https://t.co/v7hMRkaN7x

  105955229K viewsView on X
• Aug 12, 20261.8x their median

  Build log, part 1. Three months on the foundations of the DeXe platform. Numbers below — measured, not estimated. Platform stats used to take 7–12s to load. We rewrote the heaviest query behind them: 20.2s → 0.96s on the database. First load takes a few seconds if stats haven't been requested recently; after that, ~0.1s. The app got lighter: main page network requests 140 → 60, worst scroll stall in the DAO feed 247ms → 0. Measured in the browser by an automated check, not by eye. The bugs you actually hit: WalletConnect login dead-ends — fixed. Spam NFTs — filtered out of wallet views (7 of 53 on the wallets we checked, zero false positives). Network mismatch — a clear prompt instead of a blank page. The data layer: indexing unblocked for 128 BSC pools, data reads now fail over automatically instead of breaking the page. Underneath it all runs a monitoring layer: 34 checks per pass, one summary, read-only by design. The checks run in code. Our in-house AI agent only writes up what the checks find. Monitoring rule: a data source going quiet is never proof of health. That was part 1. The build log continues. #DeXe

  871267224K viewsView on X
• Jul 9, 2026

  $DEXE is available on ChangeNOW. @DexeNetwork builds DAO infrastructure for onchain governance, treasury management, delegation, launchpads and reward systems, helping communities run transparent Web3 organizations. Swap $DEXE instantly here: https://t.co/fhXAAN7zRp https://t.co/1QefKgwbsv

  902161108K viewsView on X
• Sep 1, 2026

  Use case #2: an OTC token sale, run by a DAO. Price, whitelist, per-wallet limits, cliff and vesting — all set in one proposal. Nothing leaves the treasury until members vote it through. This is what DeXe was built for. #DeXe #DAO https://t.co/gntqggW8U5

  70530317K viewsView on X

Ranked by total interactions across everything we have tracked for this account, which is a longer history than the 30-day window the rates above use. The multiple compares each post to this account's own median.

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